Application Research of CEEMDAN in Early Fault Diagnosis of Rolling Bearing

In order to solve the difficulty of extracting early fault features of rolling bearings under strong background noise, a new fault diagnosis method for rolling bearings based on complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN). Firstly, in order to enhance the impact characteristics of signals, a set of IMF components were obtained by CEEMDAN. Then kurtosis was used as the evaluation index to select the effective component to obtain recombined signal. Finally, the envelope feature of the recombined signal was analyzed to judge the fault location. The validity and superiority of the proposed method are verified compared with other methods through the experimental analysis of the rolling bearings.